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Adaptive Widely Linear Reduced-Rank Beamforming Based on Joint Iterative Optimization | IEEE Journals & Magazine | IEEE Xplore

Adaptive Widely Linear Reduced-Rank Beamforming Based on Joint Iterative Optimization


Abstract:

We propose a reduced-rank beamformer based on the rank-D Joint Iterative Optimization (JIO) of the modified Widely Linear Constrained Minimum Variance (WLCMV) problem f...Show More

Abstract:

We propose a reduced-rank beamformer based on the rank-D Joint Iterative Optimization (JIO) of the modified Widely Linear Constrained Minimum Variance (WLCMV) problem for non-circular signals. The novel WLCMV-JIO scheme takes advantage of both the Widely Linear (WL) processing and the reduced-rank concept, outperforming its linear counterpart as well as the full-rank WL beamformer. We develop an augmented recursive least squares algorithm and present an improved structured version with a much more efficient implementation. It is shown that the improved adaptive scheme achieves the best convergence performance among all the considered methods with a low computational complexity.
Published in: IEEE Signal Processing Letters ( Volume: 21, Issue: 3, March 2014)
Page(s): 265 - 269
Date of Publication: 23 December 2013

ISSN Information:


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